Given the increasing demand for mobile computing, the last decade has seen a surge in the number and types of portable or handheld computer devices. Frequently referred to as Personal Digital Assistants or PDAs, these computer devices are largely designed to function as electronic notepads, address books, daily planners and the like. As computer hardware technology has improved and miniaturized, PDAs have become increasing smaller, lighter and faster.
One tradeoff to the reduced size of PDAs is their inability to accommodate traditional keyboard-based, touch-typing data entry. Given the nature of the typically hand-held PDA, together with the physical constraints of a small viewing and data input area, keyboards are generally unacceptable as a means of data entry. As a result, many PDAs use a pen and digitizer pad combination for data input. This arrangement allows a user to hold the PDA in one hand while at the same time inputting data via the digitizer pad using the pen. PDAs have long been used for pen-based keystroke input of characters, for example, by using the pen to press icon representations of characters located on a “QWERTY” keyboard layout. More recently, PDAs have included pen-based handwritten character entry. Handwriting recognition engines have been provided that convert the user's handwriting into a machine readable format.
While both keystroke and handwritten character entry have become increasingly embraced as workable options for PDAs, there remain disadvantages with both types of PDA data entry. Character keyboards provided with PDAs have been based on a traditional QWERTY keyboard layout. But in light of the inability to use two hands to type on PDAs, there is little advantage to preserving this format over superior keyboard layouts. In addition, the traditional QWERTY keyboard layout does not efficiently provide for the inclusion of frequently used complementary characters such as numbers and certain symbols. Finally, PDAs using keyboard-based data entry fail to provide convenient and efficient movement between various keyboard options.
There are likewise disadvantages with existing PDA handwriting systems. Historically it has been very difficult to teach a computer system all of the nuances associated with interpreting a user's handwritten words. Lacking the technological resources to provide full context referencing, PDA handwriting recognition systems have relied instead almost solely on the writer's input strokes to evaluate each character separately. Natural human handwriting, however, is inherently complex, and typically involves multiple strokes to complete each character. Due to database and processor limitations, traditional PDA handwriting systems have great difficultly evaluating characters consisting of multiple strokes. Thus, rather than analyze the natural manner in which most writers produce characters, PDA handwriting manufacturers have promoted the use of short-hand or other abbreviated forms of handwriting wherein each character is represented by a single, typically simple stroke. While this approach has improved the overall accuracy of PDA handwriting systems, it has come as the expense of the user, who is now forced to learn a new language to effectively use the PDAs. In addition, PDAs historically suffer from processor delays or lag associated with handwritten data input. PDA handwriting systems are largely unable to keep pace with handwriting input. Finally, many PDA handwriting recognition systems rely heavily on the use of mode keys, which require additional strokes, to distinguish between upper and lower case letters, numbers and symbols.
Thus, there is a need for an improved system and method for pen-based handwritten and keystroke data input into a PDA that overcomes the noted disadvantages with existing systems.